<p>This tutorial shows how to use Generalized Linear Modeling in H<sub>2</sub>O for model training and classification.</p>

<p>GLM is a regression algorithm which finds a best-fit hyper-plane through the training data; GLM models have coefficients for each feature.  Logistic Regression is a variant of GLM where the magnitude of the coefficients is related to the features' predictive ability; large (absolute) magnitude means the feature predicts more strongly.</p>

<p>
Vocabulary:
<ul>
  <li><a href="http://en.wikipedia.org/wiki/General_linear_model">GLM</a></li>
  <li><a href="http://en.wikipedia.org/wiki/Dataset">Dataset</a></li>
  <li><a href="http://en.wikipedia.org/wiki/Statistical_classification">Classification</a></li>
</ul>
</p>

